Abstract Details
Activity Number:
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550
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Type:
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Contributed
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Date/Time:
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Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract - #309749 |
Title:
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Systematic Review of Methods for Individual Patient Data Meta-Analysis with Binary Outcomes
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Author(s):
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Andrea Benedetti*+ and Doneal Thomas
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Companies:
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McGill University
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Keywords:
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individual patient data ;
meta analysis ;
random effects ;
systematic review ;
heterogeneity
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Abstract:
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Meta-analyses based on individual patient data (IPD-MA) are regarded as the gold standard and are becoming increasingly common. In a review of articles published from 1999-2001, the statistical approach was seldom reported in sufficient detail, and the outcome was binary in 32% of the studies considered. Here, we review 26 IPD-MA published in 2011 that used a binary outcome to consider: the approach used in their analysis, (e.g. a one- or two-stage model), the assumptions of fixed or random effects, etc. We investigated how heterogeneity across studies was described and methods used to adjust for covariate effects. 18 of 26 IPD-MA used a one-stage approach. Random-effect logistic regression was the standard method, allowing the treatment effect to vary across studies. Most IPD-MA presented some form of statistic to measure heterogeneity across studies, usually calculated using a two-stage approach. Subgroup analyses on patient-level covariates was the general approach of analyzing the covariate- treatment interaction effects. IPD-MA with binary outcomes has increased. Methods are still often not reported in enough detail.
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